Laila Rasmy
Orcid: 0000-0002-2644-4908
According to our database1,
Laila Rasmy
authored at least 16 papers
between 2018 and 2023.
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Bibliography
2023
PheME: A deep ensemble framework for improving phenotype prediction from multi-modal data.
Proceedings of the 11th IEEE International Conference on Healthcare Informatics, 2023
Training Recurrent Neural Network-Based Model to Predict COVID-19 Patient Risk for PASC using Pytorch_EHR - Hands-on Tutorial on N3C.
Proceedings of the 11th IEEE International Conference on Healthcare Informatics, 2023
A Deep-Learning-based Two-Compartment Predictive Model (PKRNN-2CM) for Vancomycin Therapeutic Drug Monitoring.
Proceedings of the 11th IEEE International Conference on Healthcare Informatics, 2023
2022
PK-RNN-V E: A deep learning model approach to vancomycin therapeutic drug monitoring using electronic health record data.
J. Biomed. Informatics, 2022
Pancreatic cancer risk prediction using recurrent neural network models trained on electronic health records and claims data.
Proceedings of the AMIA 2022, 2022
2021
Automatic Sub-Pixel Co-Registration of Remote Sensing Images Using Phase Correlation and Harris Detector.
Remote. Sens., 2021
Med-BERT: pretrained contextualized embeddings on large-scale structured electronic health records for disease prediction.
npj Digit. Medicine, 2021
Simple Recurrent Neural Networks is all we need for clinical events predictions using EHR data.
CoRR, 2021
CovRNN: predicting outcomes of COVID-19 patients on admission using their electronic health records with minimal data processing.
Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021
Generalizable Gated Recurrent Neural Network based model to predict COVID-19 patient outcomes on admission.
Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021
2020
Representation of EHR data for predictive modeling: a comparison between UMLS and other terminologies.
J. Am. Medical Informatics Assoc., 2020
Med-BERT: pre-trained contextualized embeddings on large-scale structured electronic health records for disease prediction.
CoRR, 2020
2019
Time-sensitive clinical concept embeddings learned from large electronic health records.
BMC Medical Informatics Decis. Mak., 2019
2018
A study of generalizability of recurrent neural network-based predictive models for heart failure onset risk using a large and heterogeneous EHR data set.
J. Biomed. Informatics, 2018